Rural Income Generation and Diversification - A Case Study ... - Doria

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The categorisation of households according to their income-mix strategies (see Chapter
6.1.7) was used as a basis for the specification and estimation of a multinomial logit model 52
for the likelihood of belonging to one of the income groups. The variables used in the equations
comprised human capital (sex, age and education of the household head, number of
adults and number of children), physical capital (size of cultivated land, distance to the nearest
market), natural capital (dummy for the Mambwe district), and a proxy for social capital
(participation).
The resulting coefficients (Table 21) showed that the likelihood of adopting either "the crop -
forest, wage, transfer" (Group CFWT) strategy or "the mixed" strategy (Group MIX) compared
to the currently most common "pure crop" strategy (Group C) was significantly determined
by the size of cultivated land: the smaller the area of cultivated land, the more probable
it was for it to belong to Group CFWT or MIX, rather than Group C. A high number of
children in the household also increased the probability of its belonging to Group MIX versus
Group C.
The likelihood of belonging to the income-portfolio Group CL, "the crop-livestock group",
increased the higher the participation rate, while having a younger household head and being
located in the Mambwe district increased the probability of falling into Group CB, "the cropbusiness”
group.
Since the multinomial logit analysis generated only a few significant coefficients, it could be
assumed that the categorisation of non-farm income sources in terms of being pushed to
(forestry, piecework and transfers) and pulled (business activities) is to some extent artificial.
There was more heterogeneity than anticipated amongst the “push” and “pull” sources: for
example collecting and selling forest products was a coping strategy for a majority of households,
while some of the wealthier ones were able to generate substantial income by selling
higher-value forest products such as sawn timber. The same applies to business activities: the
poorest households ran businesses that tended to produce poor returns such as petty trade,
while the better-off could invest in more profitable enterprises. The transfers included food
aid targeted at the most vulnerable households, and remittances from relatives usually received
by the wealthier households.
The size of cultivated land as such or in relation to the number of adults in the household
was a common denominator in many of the results: it seems to have a strong influence on
income-generation and diversification capacity and patterns. Since land is available and
households cultivate less than they actually possess, endogenous and exogenous factors determining
the capacity to cultivate seem to be critical to income generation.
52 The multinomial logit model was an application of the models used by Schmidt and Strauss (1995), Dercon
and Krishnan (1996), Woldenhanna and Oskam (2001), Berhanu et al. (2007) and Bigsten and Tengstam
(2008).